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RISS 인기검색어
- 검색키워드
- 저자 : L. GUENFAF (검색결과 4 건)
- 무료
- 기관 내 무료
- 유료
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Flux Oriented Control of Active Mass Damper Induction Motor for Buildings Under Seismic Excitation
L. Guenfaf,S. Allaoua 제어로봇시스템학회 2015 제어로봇시스템학회 국제학술대회 논문집 Vol.2015 No.10
This study investigated a flux oriented control of Active Mass Damper (AMD) induction motor for buildings under seismic ground motion. Composed primarily of an induction motor, a mass bloc and a ball screw, the electric-type active mass damper (AMD) system is free from noise problems, oil leakage, and labor-intensive maintenance that commonly are associated with hydraulic AMD systems. In this study a five steel-frame structure is implemented with the electric type AMD system. An LQR control algorithm is adopted for displacement reduction of the structure subjected to ground acceleration. The indirect flux oriented control method is used for the control of the AMD induction motor. The great advantage of this method resides in the fact that we do not need to use the amplitude of the rotor flux but only its position. Numerical simulation is performed under the conditions of a Kanai-Tajimi power spectral density function of ground motion and the simulation results show that the torque supplied by the induction motor pursuits its reference provided by the LQR control algorithm. Significant reductions of 65% and 78% respectively in the roof acceleration and roof displacement have been reached. And the proposed system is recommended for practical implementation.
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Neuro-Generalized Minimum Variance Controller Applied To Earthquake Engineering Problems
L. GUENFAF,M. DJEBIRI 제어로봇시스템학회 2011 제어로봇시스템학회 국제학술대회 논문집 Vol.2011 No.10
This paper presents a neural network-based control method applied to civil engineering structures. The neural network learns the control task from an already existing controller, which is the generalized minimum variance (GMV) controller. The objective is to take advantage of the generalization capabilities and the nonlinear behavior of neural networks in order to overcome the limitations of the existing controller and even to improve its performances. Simulation results demonstrate the effectiveness of the neural network controller and its capability to compensate for structural parameter variations.
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Gain Scheduling GMV using Gaussian Function for Nonlinear hysteretic Structural Systems
L. GUENFAF,S. ALLAOUA,M. DJEBIRI,M.S. BOUCHERIT,F. BOUDJEMA 제어로봇시스템학회 2012 제어로봇시스템학회 국제학술대회 논문집 Vol.2012 No.10
In this paper, a generalized minimum variance algorithm using the gain scheduling technique is presented. First, we linearize the nonlinear model of the structure around a number of desired states representing regions of evolution of the structural response. Around each state, an Auto-Regressive-Moving-Average-eXogen (ARMAX) model of the structure is determined and a local GMV control law is developed. The control consists on switching-on or switching-off a local GMV controller depending on the actual state of the system. The approach consists on using gaussian membership functions related to the domains around the points of linearization. The control from the local GMV controllers is weighed by these functions and added together to produce the final control.
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Linear Quadratic AMD Controller with an Observer for Buildings under Seismic Ground Motion
L. Guenfaf,S. Allaoua 제어로봇시스템학회 2013 제어로봇시스템학회 국제학술대회 논문집 Vol.2013 No.10
This paper is devoted to the study of active control with an observer for the control of structural vibration using an electric servomotor active mass driver (AMD) system. Composed primarily of an electric servomotor and a ball screw, the electrical AMD system is free from noise problems, oil leakage, and labor-intensive maintenance that commonly are associated with hydraulic AMD systems. For technological reasons and for cost reasons the number of sensors is limited by using the Luenberger observer. This observer is based on the synthesis of a static gain to stabilize the error state estimation and the convergence of the observer status to the state of the real system. In this study an instantaneous linear quadratic control algorithm is adopted using an observer. Numerical simulation is performed using a single sensor on the top floor of a five-story steel frame structure under the conditions of a Kanai-Tajimi power spectral density function of ground acceleration.
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